Locus-specific databases and recommendations to strengthen their contribution to the classification of variants in cancer susceptibility genes.
Locus-specific databases (LSDBs) are curated collections of sequence variants in genes associated with disease. LSDBs of cancer-related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play an important role in disseminating clinical classification of variants. The IARC Working Group on Unclassified Genetic Variants has proposed a new system of five classes of variants in cancer susceptibility genes. However, standards are lacking for reporting and analyzing the multiple data types that assist in classifying variants. By adhering to standards of transparency and consistency in the curation and annotation of data, LSDBs can be critical for organizing our understanding of how genetic variation relates to disease. In this article we discuss how LSDBs can accomplish these goals, using existing databases for BRCA1, BRCA2, MSH2, MLH1, TP53, and CDKN2A to illustrate the progress and remaining challenges in this field. We recommend that: 1) LSDBs should only report a conclusion related to pathogenicity if a consensus has been reached by an expert panel. 2) The system used to classify variants should be standardized. The Working Group encourages use of the five class system described in this issue by Plon and colleagues. 3) Evidence that supports a conclusion should be reported in the database, including sources and criteria used for assignment. 4) Variants should only be classified as pathogenic if more than one type of evidence has been considered. 5) All instances of all variants should be recorded.
Greenblatt
Marc S
MS
Vermont Cancer Center and Department of Medicine, University of Vermont, Burlington, Vermont 05405, USA. Marc.Greenblatt@vtmednet.org
Brody
Lawrence C
LC
Foulkes
William D
WD
Genuardi
Maurizio
M
Hofstra
Robert M W
RM
Olivier
Magali
M
Plon
Sharon E
SE
Sijmons
Rolf H
RH
Sinilnikova
Olga
O
Spurdle
Amanda B
AB
D019295:Computational Biology / Q000379:methods*; D003625:Data Collection / Q000379:methods; D030541:Databases, Genetic / Q000592:standards*; D052138:Genes, Neoplasm; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D006801:Humans; D009386:Neoplastic Syndromes, Hereditary / Q000145:classification* / Q000235:genetics